Design of Intelligent Transportation Light Based on Deep Learning
In view of the inflexibility of the passage time in traditional transportation light,an intelligent transportation light based on Deep Learning is designed through research on the traffic flow information collected under the transportation light.Firstly,the lane lines are extracted using FCN,and a clustering algorithm is used to fit the lane line function.Secondly,the SSD network model is extracted,with the VGG network as the backbone feature of model,to detect the positional information of vehicles,and the positional information of vehicles is combined with the positional information of lane lines to count the traffic flow information of each lane under the transportation light.The experimental results show that the intelligent transportation light system based on Deep Learning has an accuracy of 90.69%in the actual application process,which is basically applied in the real environment.
国家科技期刊平台
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